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Sensors 2018, 18(7), 2240; https://doi.org/10.3390/s18072240

Improved ABC Algorithm Optimizing the Bridge Sensor Placement

1
School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
2
School of Mechatronic Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
*
Author to whom correspondence should be addressed.
Received: 29 May 2018 / Revised: 5 July 2018 / Accepted: 6 July 2018 / Published: 11 July 2018
(This article belongs to the Special Issue Bridge Structural Health Monitoring and Damage Identification)
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Abstract

Inspired by sensor coverage density and matching & preserving strategy, this paper proposes an Improved Artificial Bee Colony (IABC) algorithm which is designed to optimize bridge sensor placement. We use dynamic random coverage coding method to initialize colony to ensure the diversity and effectiveness. In addition, we randomly select the factors with lower trust value to search and evolve after food source being matched in order that the relatively high trust point factor is retained in the exploitation of food sources, which reduces the blindness of searching and improves the efficiency of convergence and the accuracy of the algorithm. According to the analysis of the modal data of the Ha-Qi long span railway bridge, the results show that IABC algorithm has faster convergence rate and better global search ability when solving the optimal placement problem of bridge sensor. The final analysis results also indicate that the IABC’s solution accuracy is 76.45% higher than that of the ABC algorithm, and the solution stability is improved by 86.23%. The final sensor placement mostly covers the sensitive monitoring points of the bridge structure and, in this way, the IABC algorithm is suitable for solving the optimal placement problem of large bridge and other structures. View Full-Text
Keywords: sensor placement; artificial bee colony algorithm; dynamic random coverage coding; matching & preserving strategy; Ha-Qi long span railway bridge sensor placement; artificial bee colony algorithm; dynamic random coverage coding; matching & preserving strategy; Ha-Qi long span railway bridge
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Yang, J.; Peng, Z. Improved ABC Algorithm Optimizing the Bridge Sensor Placement. Sensors 2018, 18, 2240.

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